Transform Factory Documents into Your AI Sales Agent's Knowledge

Accuracy depends on document quality. Clean spec sheets typically see 80-90% auto-approve rates. Scanned documents and handwritten notes are lower but still useful with human review.

Product images are deep-classified by AI (identifying colors, materials, dimensions) and automatically cropped into 4 web-optimized variants. They're stored in your media library and can be used across your website, emails, and blog posts.

Yes. The AI vision and NLP engines handle Chinese, Spanish, and most major languages. Extracted data is structured in English for the knowledge base, regardless of source language.

The core extraction and structuring process typically completes in days, not months. The timeline depends on document volume and complexity. Once processed, high-confidence data (≥85%) auto-approves and is immediately available for your AI agent via a one-click push to the knowledge base.

Yes, our Gemini Vision engine can process challenging inputs like handwritten notes and low-quality scans. Accuracy is lower compared to clean digital documents, but the system still extracts useful data. All low-confidence extractions are flagged for human review to ensure quality before the information is published.

Product images undergo advanced processing. They are deep-classified with structured data (colors, materials, dimensions) and automatically cropped into 4 ready-to-use variants: thumbnail, card, hero, and email sizes. This creates an organized media library for your website and marketing materials.

Processing is fast. For clean documents like digital PDFs or Excel files, data extraction and auto-approval (for entries with ≥85% confidence) happen in minutes. The entire workflow—from upload to having a populated knowledge base for your AI sales agent—typically takes days, not the months required for manual data entry.

Yes, but with a different workflow. Our Gemini Vision engine is advanced, but accuracy depends on document quality. For handwritten notes or low-resolution scans, the system will assign a lower confidence score and route those extractions for human review. This ensures your knowledge base remains accurate while still capturing valuable data from imperfect sources.

Extracted data is structured and presented in a review interface. High-confidence entries (≥85%) auto-approve. You can review, edit, or approve lower-confidence items. With one click, all approved data is pushed directly into your OwnlyBrand knowledge base. Product images are also processed into four optimized sizes with metadata, ready for your website and sales materials.

IDP cuts costs by automating data extraction, reducing manual labor from $18 per document to $2.50. It also slashes error rates from 6% to 0.3%, eliminating rework costs. For a factory processing 10,000 documents annually, this saves $155,000 per year.

Payback typically occurs within 6-12 months at volumes above 500 documents per month. Factories processing over 2,000 documents monthly see payback in under 6 months. Setup costs range from $5,000 to $20,000, with ongoing maintenance at 15-20% of license fees.